JMIR Publications

ABSTRACT

Background:

Seasonal influenza activity showed a sharp decline in activity at the beginning of the Corona Virus Disease 2019 (COVID-19) emergence. Whether there is an epidemiological correlation between the dynamic of two respiratory infectious diseases and their future trends needs to be explored.

Objective:

To assess the correlation between COVID-19 and influenza activity and estimate their upcoming epidemiological trends.

Methods:

We retrospectively described the dynamics of COVID-19 and influenza in six World Health Organization (WHO) regions from January 2020-March 2023, and used the long short-term memory (LSTM) machine learning model to learn potential patterns of previously observed activity to predict trends for the next sixteen weeks. Finally, the past and future correlation in epidemiology between two respiratory infectious diseases was assessed by the Spearman correlation coefficients.

Results:

With the emergence of original strain and other severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, influenza activity kept below 10% for more than one year in the six WHO regions. Subsequently, it gradually rose as the Delta activity dropped, but still peaked below Delta. During the Omicron pandemic and the upcoming period, the two increased as each other's activity decreased, becoming interactively dominant more than once and lasting 3-4 months. Correlation analysis showed that COVID-19 and influenza activity presented a predominantly negative correlation with coefficients above -0.3 in WHO regions, especially during the Omicron pandemic and the estimated upcoming period. They had a transient positive correlation in the European Region of WHO (EURO), and the Western Pacific Region of WHO (WPRO) when multiple dominant strains were mixed pandemic.

Conclusions:

Influenza activity and former seasonal epidemiological patterns are shaken by the COVID-19 pandemic. Their activities are moderately and above inversely correlated, oppressing and competing with each other, showing a seesaw effect. In the post-pandemic era of COVID-19, the seesaw trends may be more prominent, prompting the possibility of using one another as early warning signals for future estimates and conducting optimized annual vaccine campaigns.